Epilogue to the Gerald Maggiora Festschrift: a tribute to an exemplary mentor, colleague, collaborator, and innovator.

In May 2022, JCAMD published a Special Issue in honor of Gerald (Gerry) Maggiora, whose scientific leadership over many decades advanced the fields of computational chemistry and chemoinformatics for drug discovery. Along the way, he has impacted many researchers in both academia and the pharmaceutical industry. In this Epilogue, we explain the origins of the Festschrift and present a series of first-hand vignettes, in approximate chronological sequence, that together paint a picture of this remarkable man. Whether they highlight Gerry's endless curiosity about molecular life sciences or his willingness to challenge conventional wisdom or his generous support of junior colleagues and peers, these colleagues and collaborators are united in their appreciation of his positive influence. These tributes also reflect key trends and themes during the evolution of modern drug discovery, seen through the lens of people who worked with a visionary leader. Junior scientists will find an inspiring roadmap for creative collegiality and collaboration.

Expanding the informational chemistries of life: peptide/RNA networks.

The RNA world hypothesis simplifies the complex biopolymer networks underlining the informational and metabolic needs of living systems to a single biopolymer scaffold. This simplification requires abiotic reaction cascades for the construction of RNA, and this chemistry remains the subject of active research. Here, we explore a complementary approach involving the design of dynamic peptide networks capable of amplifying encoded chemical information and setting the stage for mutualistic associations with RNA. Peptide conformational networks are known to be capable of evolution in disease states and of co-opting metal ions, aromatic heterocycles and lipids to extend their emergent behaviours. The coexistence and association of dynamic peptide and RNA networks appear to have driven the emergence of higher-order informational systems in biology that are not available to either scaffold independently, and such mutualistic interdependence poses critical questions regarding the search for life across our Solar System and beyond.This article is part of the themed issue 'Reconceptualizing the origins of life'.

Digital and analog chemical evolution.

Living matter is the most elaborate, elegant, and complex hierarchical material known and is consequently the natural target for an ever-expanding scientific and technological effort to unlock and deconvolute its marvelous forms and functions. Our current understanding suggests that biological materials are derived from a bottom-up process, a spontaneous emergence of molecular networks in the course of chemical evolution. Polymer cooperation, so beautifully manifested in the ribosome, appeared in these dynamic networks, and the special physicochemical properties of the nucleic and amino acid polymers made possible the critical threshold for the emergence of extant cellular life. These properties include the precise and geometrically discrete hydrogen bonding patterns that dominate the complementary interactions of nucleic acid base-pairing that guide replication and ensure replication fidelity. In contrast, complex and highly context-dependent sets of intra- and intermolecular interactions guide protein folding. These diverse interactions allow the more analog environmental chemical potential fluctuations to dictate conformational template-directed propagation. When these two different strategies converged in the remarkable synergistic ribonucleoprotein that is the ribosome, this resulting molecular digital-to-analog converter achieved the capacity for both persistent information storage and adaptive responses to an ever-changing environment. The ancestral chemical networks that preceded the Central Dogma of Earth's biology must reflect the dynamic chemical evolutionary landscapes that allowed for selection, propagation, and diversification and ultimately the demarcation and specialization of function that modern biopolymers manifest. Not only should modern biopolymers contain molecular fossils of this earlier age, but it should be possible to use this information to reinvent these dynamic functional networks. In this Account, we review the first dynamic network created by modification of a nucleic acid backbone and show how it has exploited the digital-like base pairing for reversible polymer construction and information transfer. We further review how these lessons have been extended to the complex folding landscapes of templated peptide assembly. These insights have allowed for the construction of molecular hybrids of each biopolymer class and made possible the reimagining of chemical evolution. Such elaboration of biopolymer chimeras has already led to applications in therapeutics and diagnostics, to the construction of novel nanostructured materials, and toward orthogonal biochemical pathways that expand the evolution of existing biochemical systems. The ability to look beyond the primordial emergence of the ribosome may allow us to better define the origins of chemical evolution, to extend its horizons beyond the biology of today and ask whether evolution is an inherent property of matter unbounded by physical limitations imposed by our planet's diverse environments.

Chemical control of peptide material phase transitions.

Progressive solute-rich polymer phase transitions provide pathways for achieving ordered supramolecular assemblies. Intrinsically disordered protein domains specifically regulate information in biological networks via conformational ordering. Here we consider a molecular tagging strategy to control ordering transitions in polymeric materials and provide a proof-of-principle minimal peptide phase network captured with a dynamic chemical network.

Design of multi-phase dynamic chemical networks.

Template-directed polymerization reactions enable the accurate storage and processing of nature's biopolymer information. This mutualistic relationship of nucleic acids and proteins, a network known as life's central dogma, is now marvellously complex, and the progressive steps necessary for creating the initial sequence and chain-length-specific polymer templates are lost to time. Here we design and construct dynamic polymerization networks that exploit metastable prion cross-ß phases. Mixed-phase environments have been used for constructing synthetic polymers, but these dynamic phases emerge naturally from the growing peptide oligomers and create environments suitable both to nucleate assembly and select for ordered templates. The resulting templates direct the amplification of a phase containing only chain-length-specific peptide-like oligomers. Such multi-phase biopolymer dynamics reveal pathways for the emergence, self-selection and amplification of chain-length- and possibly sequence-specific biopolymers.

Influence of molecular flexibility and polar surface area metrics on oral bioavailability in the rat.

The relationship of rotatable bond count (N(rot)) and polar surface area (PSA) with oral bioavailability in rats was examined for 434 Pharmacia compounds and compared with an earlier report from Veber et al. (J. Med. Chem. 2002, 45, 2615). N(rot) and PSA were calculated with QikProp or Cerius2. The resulting correlations depended on the calculation method and the therapeutic class within the data superset. These results underscore that such generalizations must be used with caution.

Solubility and permeability measurement and applications in drug discovery.

Solubility and cellular permeability are two of the most important biopharmaceutical properties impacting the successful development of drug substances. Given the importance of these properties, most pharmaceutical companies have invested in medium to high throughput technologies for early evaluation of these characteristics in the drug discovery funnel in order to select, prioritize or eliminate compounds with unfavorable solubility and/or permeability. However, these technologies require physical samples of the substances to be tested. In order to facilitate the early stages of drug discovery, such as defining compound collection composition, designing combinatorial libraries, and in hit expansion or lead optimization, models for predicting aqueous solubility and permeability in the absence of physical sample are increasingly being employed. In this overview, we will discuss solubility and permeability experimental and computational methods separately and then interrelate them in physiologically relevant models for predicting in vivo performance.

In silico predictions of blood-brain barrier penetration: considerations to "keep in mind".

Within drug discovery, it is desirable to determine whether a compound will penetrate and distribute within the central nervous system (CNS) with the requisite pharmacokinetic and pharmacodynamic performance required for a CNS target or if it will be excluded from the CNS, wherein potential toxicities would mitigate its applicability. A variety of in vivo and in vitro methods for assessing CNS penetration have therefore been developed and applied to advancing drug candidates with the desired properties. In silico methods to predict CNS penetration from chemical structures have been developed to address virtual screening and prospective design. In silico predictive methods are impacted by the quality, quantity, sources, and generation of the measured data available for model development. Key considerations for predictions of CNS penetration include the comparison of local (in chemistry space) versus global (more structurally diverse) models and where in the drug discovery process such models may be best deployed. Preference should also be given to in vitro and in vivo measurements of greater mechanistic clarity that better support the development of structure-property relationships. Although there are numerous statistical methods that have been brought to bear on the prediction of CNS penetration, a greater concern is that such models are appropriate for the quality of measured data available and are statistically validated. In addition, the assessment of prediction uncertainty and relevance of predictive models to structures of interest are critical. This article will address these key considerations for the development and application of in silico methods in drug discovery.

Predicting drug absorption: how nature made it a difficult problem.

Significant recent work has focused on predicting drug absorption from structure. Several misperceptions regarding the nature of absorption seem to be common. Among these is that intestinal absorption, permeability, fraction absorbed, and, in some cases, even bioavailability, are equivalent properties and can be used interchangeably. A second common misperception is that absorption, permeability, etc. are discrete, fundamental properties of the molecule and can be predicted solely from some structural representation of the drug. In reality, drug absorption is a complex process dependent upon drug properties such as solubility and permeability, formulation factors, and physiological variables, including regional permeability differences, pH, lumenal and mucosal enzymology, and intestinal motility, among others. This article will explore the influence of these different variables on drug absorption and the implications with regards to attempting to develop predictive drug absorption algorithms.